Why are some states doing so poorly on the AHR?

This analysis seeks to explore the relationship between the finance score and the costs associated with transportation construction and maintenance in urban vs rural states

## Rows: 750 Columns: 28
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (14): ., Report Edition, Rural Interstate Poor Condition, Number of Mile...
## dbl  (1): Year
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

Sum of Spending in All States

Year Total_Spending Admin_Spending Maint_Spending Capital_Spending
2005 $98,905,495.00 $6,359,601.00 $15,944,218.00 $50,309,238.00
2006 $99,609,053.00 $7,015,900.00 $17,071,805.00 $54,662,456.00
2007 $109,714,183.00 $7,914,254.00 $20,004,734.00 $62,570,465.00
2008 $118,364,945.00 $10,777,381.00 $18,707,307.00 $62,906,654.00
2009 $117,691,336.00 $9,247,068.00 $20,762,054.00 $65,102,982.00
2011 $124,160,011.00 $8,486,420.00 $20,446,877.00 $66,595,966.00
2012 $132,078,139.00 $8,614,245.00 $21,235,771.00 $70,152,840.00
2013 $131,216,540.00 $8,191,756.00 $21,187,578.00 $68,864,703.00
2014 $142,130,109.00 $8,155,604.00 $22,519,783.00 $74,336,715.00
2015 $145,013,710.00 $8,845,187.00 $22,812,987.00 $74,895,863.00
2016 $139,114,797.00 $8,805,149.00 $23,334,525.00 $71,752,847.00
2018 $151,785,475.00 $9,520,230.00 $26,554,566.00 $77,145,873.00
2019 $157,763,506.00 $10,083,635.00 $27,457,186.00 $78,869,455.00
##      Total_increase Admin_increase Maint_increase Capit_increase
## [1,] 59.51%         58.56%         72.21%         56.77%
Spending (in Millions) per Lane Mile
Year Mean_Total_Spending Mean_Admin_Spending Mean_Maint_Spending Mean_Capital_Spending
2005 96.70780 6.296430 15.59245 44.12532
2006 76.77893 5.658905 11.29937 39.02704
2007 78.61012 6.567648 13.32362 41.83878
2008 82.21688 7.914406 13.06733 42.66494
2009 87.35376 7.662852 14.46659 45.72699
2011 94.40735 7.192401 14.19572 48.72561
2012 103.43915 7.456157 14.43227 51.42967
2013 100.63841 7.143515 15.21878 49.80954
2014 123.40047 7.781953 18.86065 61.22979
2015 105.90247 7.250358 15.71685 52.22496
2016 90.71018 6.704275 14.46514 45.11075
2018 94.86940 6.442822 15.95184 46.80493
2019 118.78649 7.330004 18.45981 54.64471
Year Total_Variance Admin_Variance Maint_Variance Capit_Variance
2005 18218.899 52.39913 686.95808 2054.256
2006 8874.264 37.50792 79.12639 1107.241
2007 5723.053 45.74173 132.53958 1364.343
2008 5920.812 76.29864 115.79198 1313.300
2009 6778.307 65.26375 200.63166 1203.428
2011 11791.261 51.55652 182.51441 2540.036
2012 14101.667 60.26171 155.74347 2462.963
2013 16028.808 56.81206 233.66495 2767.747
2014 32577.252 67.37673 480.96445 5459.697
2015 14760.678 55.30855 190.07772 3073.081
2016 7032.262 45.93955 136.12711 1378.899
2018 9148.768 32.97870 186.88097 1848.760
2019 27817.718 35.38823 261.20032 2738.361

## # A tibble: 13 × 5
##     Year Total_Variance Admin_Variance Maint_Variance Capit_Variance
##    <dbl>          <dbl>          <dbl>          <dbl>          <dbl>
##  1  2005           6.30           4.38          9.14           2.74 
##  2  2006           3.05           2.60          0.926          1.26 
##  3  2007           1.63           2.50          1.13           1.19 
##  4  2008           1.45           2.26          1.14           1.14 
##  5  2009           1.68           2.62          1.60           0.976
##  6  2011           2.66           2.48          1.52           1.99 
##  7  2012           2.81           2.83          1.20           1.74 
##  8  2013           3.26           2.96          1.82           2.04 
##  9  2014           5.13           3.23          3.02           3.15 
## 10  2015           2.47           2.48          1.28           1.92 
## 11  2016           1.40           2.28          0.963          1.03 
## 12  2018           1.71           1.56          1.14           1.33 
## 13  2019           3.97           1.24          1.23           1.56

Greater Variance In Finance Scores than Performance Scores

New Jersey has by far the worst Finance Score, almost double

## Rows: 50 Columns: 43
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr  (1): State
## dbl (42): Urbanization, Tax Burden Overall, Property Tax Burden, Income Tax ...
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
##             State Finance Score Performance Score
## 30     New Jersey         7.884             1.758
## 32       New York         3.157             1.322
## 21  Massachusetts         2.960             0.971
## 47     Washington         2.924             0.967
## 8        Delaware         2.780             1.060
## 39   Rhode Island         2.718             2.018
## 9         Florida         2.632             0.753
## 5      California         2.422             1.299
## 20       Maryland         2.102             0.876
## 7     Connecticut         2.022             0.632
## 11         Hawaii         1.824             2.230
## 38   Pennsylvania         1.413             1.216
## 28         Nevada         1.409             0.590
## 3         Arizona         1.398             0.879
## 45        Vermont         1.398             0.438
## 13       Illinois         1.391             1.249
## 6        Colorado         1.379             1.158
## 14        Indiana         1.333             0.956
## 37         Oregon         1.305             0.749
## 36       Oklahoma         1.303             1.181
## 2          Alaska         1.254             2.586
## 29  New Hampshire         1.238             0.622
## 35           Ohio         1.220             0.757
## 1         Alabama         1.151             0.869
## 44           Utah         1.138             0.449
## 23      Minnesota         1.103             0.668
## 10        Georgia         1.062             0.630
## 22       Michigan         1.048             1.181
## 49      Wisconsin         1.018             0.898
## 42      Tennessee         0.807             0.643
## 43          Texas         0.799             0.789
## 12          Idaho         0.777             0.644
## 15           Iowa         0.764             0.938
## 31     New Mexico         0.716             1.052
## 19          Maine         0.621             1.323
## 46       Virginia         0.585             0.511
## 16         Kansas         0.555             0.730
## 41   South Dakota         0.554             0.755
## 33 North Carolina         0.517             0.684
## 18      Louisiana         0.516             1.525
## 50        Wyoming         0.489             0.825
## 27       Nebraska         0.447             1.062
## 24    Mississippi         0.434             0.924
## 4        Arkansas         0.392             0.984
## 17       Kentucky         0.392             0.725
## 26        Montana         0.392             0.829
## 25       Missouri         0.368             0.698
## 40 South Carolina         0.346             1.130
## 34   North Dakota         0.297             0.608
## 48  West Virginia         0.263             1.389

Finance STDV, Variance

## [1] 1.231537
## [1] 1.516683

Performance STDV, Variance

## [1] 0.4358104
## [1] 0.1899307

Tax, Finance, and Performance Ranking Matrix

Shows the correlations between all rankings Notice that Finance Rank correlates with both cost of living and doing business but nothing else. Neither is correlated with performance rank either.

## Rows: 50 Columns: 28
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## dbl (28): Tax Overall Rank, Finance Rank, Performance Rank, Overall Rank, Ca...
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

Multiple Regression Analysis

Explores statistical relationships between Finance, Performance, and Localized Costs Ranks

Here’s the CNBC Definitions:

Overall Rank

## Rows: 50 Columns: 43
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr  (1): State
## dbl (42): Urbanization, Tax Burden Overall, Property Tax Burden, Income Tax ...
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.
## 
## Call:
## lm(formula = Overall.Rank ~ EDUCATION + WORKFORCE + Cost.of.Doing.Business + 
##     Cost.of.Living)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -19.299  -9.618   0.431   9.028  19.268 
## 
## Coefficients:
##                        Estimate Std. Error t value Pr(>|t|)  
## (Intercept)             3.80518    7.30313   0.521   0.6049  
## EDUCATION               0.30566    0.11994   2.549   0.0143 *
## WORKFORCE              -0.09737    0.12634  -0.771   0.4449  
## Cost.of.Doing.Business  0.59189    0.22959   2.578   0.0133 *
## Cost.of.Living          0.05580    0.22069   0.253   0.8016  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 11.46 on 45 degrees of freedom
## Multiple R-squared:  0.4325, Adjusted R-squared:  0.3821 
## F-statistic: 8.574 on 4 and 45 DF,  p-value: 3.124e-05

Finance Rank

## 
## Call:
## lm(formula = Finance.Rank ~ EDUCATION + WORKFORCE + Cost.of.Doing.Business + 
##     Cost.of.Living)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -25.8019  -4.9936  -0.5732   8.1290  21.9406 
## 
## Coefficients:
##                         Estimate Std. Error t value Pr(>|t|)   
## (Intercept)            18.325130   6.676857   2.745  0.00867 **
## EDUCATION               0.007867   0.109650   0.072  0.94312   
## WORKFORCE              -0.302485   0.115503  -2.619  0.01198 * 
## Cost.of.Doing.Business  0.270176   0.209906   1.287  0.20463   
## Cost.of.Living          0.302632   0.201768   1.500  0.14062   
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 10.48 on 45 degrees of freedom
## Multiple R-squared:   0.53,  Adjusted R-squared:  0.4882 
## F-statistic: 12.69 on 4 and 45 DF,  p-value: 5.418e-07

RPP + Overall Score

## 
## Call:
## lm(formula = Overall.Score ~ RPP)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.75755 -0.26877 -0.04288  0.16320  1.74333 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) -2.899159   0.645515  -4.491 4.45e-05 ***
## RPP          0.041369   0.006647   6.223 1.14e-07 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.4206 on 48 degrees of freedom
## Multiple R-squared:  0.4466, Adjusted R-squared:  0.435 
## F-statistic: 38.73 on 1 and 48 DF,  p-value: 1.142e-07

******* Finance Score + RPP ************

## 
## Call:
## lm(formula = Finance.Score ~ RPP)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -1.6549 -0.4306 -0.0728  0.1464  4.7173 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) -7.80692    1.37410  -5.681 7.66e-07 ***
## RPP          0.09460    0.01415   6.685 2.23e-08 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.8954 on 48 degrees of freedom
## Multiple R-squared:  0.4822, Adjusted R-squared:  0.4714 
## F-statistic: 44.69 on 1 and 48 DF,  p-value: 2.234e-08

Finance Score + Performance + RPP

## 
## Call:
## lm(formula = Finance.Score ~ Performance.Score + RPP)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -1.8950 -0.3498 -0.0387  0.1381  4.5961 
## 
## Coefficients:
##                   Estimate Std. Error t value Pr(>|t|)    
## (Intercept)       -7.60083    1.39511  -5.448 1.82e-06 ***
## Performance.Score  0.28747    0.31612   0.909    0.368    
## RPP                0.08951    0.01524   5.873 4.18e-07 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.897 on 47 degrees of freedom
## Multiple R-squared:  0.4911, Adjusted R-squared:  0.4695 
## F-statistic: 22.68 on 2 and 47 DF,  p-value: 1.275e-07

Cost of Living vs Tax Burden

## New names:
## * `` -> ...3
## Rows: 510 Columns: 4
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (2): City, State
## dbl (1): Cost of Living Index
## lgl (1): ...3
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

## No trace type specified:
##   Based on info supplied, a 'scatter' trace seems appropriate.
##   Read more about this trace type -> https://plotly.com/r/reference/#scatter
## No trace type specified:
##   Based on info supplied, a 'scatter' trace seems appropriate.
##   Read more about this trace type -> https://plotly.com/r/reference/#scatter

Results

The above results show that when controlling for differences in Workforce and Education, the cost of doing business has a significant impact on the Overall Score, which is the best indicator